Download all Technical Policy Briefing Notes in a single ... - Mediation

Key Messages• There is increasing interest in the appraisal ofoptions, as adaptation moves from theory topractice. In response, a number of existingand new decision support tools are beingconsidered, including methods that addressuncertainty.• The FP7 MEDIATION project has undertaken adetailed review of these tools, and has testedthem in a series of case studies. It hasassessed their applicability for adaptation andanalysed how they consider uncertainty. Thefindings have been used to provideinformation and guidance for the MEDIATIONAdaptation Platform and are summarised in aset of policy briefing notes.• One of the tools widely recommended foradaptation is Robust Decision Making(RDM). RDM aims to identify robust optionsor strategies, i.e. those which perform wellover a wide range of futures. It aims tosupport decision making under conditions ofdeep uncertainty, i.e. when little or noprobabilistic information is available.• RDM has been widely applied as analytic,scenario-based approach for decisionsupport. The formal application is undertakenin a computer modelling interface that adoptsdata sampling algorithms to analysestrategies over very large ensembles.However, the concepts of the approach canalso be used in a simpler application, whichtests how options or strategies performagainst climate uncertainty.• RDM has high relevance for adaptation, andaligns strongly with the concepts of adaptivemanagement, by targeting policies or optionsthat are robust rather than optimal.• The review has considered the strengths andweakness of the approach for adaptation. Thekey strength is the quantitative analysis ofrobustness, and the fact that the method canbe applied when future uncertainties are poorlycharacterised or probabilistic information islimited or unavailable. The approach can alsowork with quantitative or economic data.• The potential weaknesses of the formalapplication relate to the high data andresource needs (for quantitative information,computing power, stakeholder engagementand analysis) and the associated expert inputrequired. The data and scenario inputs canalso be somewhat subjective, influenced bystakeholders’ perception. However, many ofthese aspects can be overcome with informalapplications of the approach, particularlywhen focused on climate uncertainty alone.• Previous applications of ROA for adaptationhave been reviewed, and adaptation casestudies are summarised. Most of the recentadaptation applications have focused onwater management, and these include bothformal and informal examples.• The review and case studies provide usefulinformation on the types of adaptationproblem types where RDM might beappropriate, as well as data needs, resourcerequirements and good practice lessons.RDM is particularly applicable undersituations of high uncertainty, whereprobabilistic information is low or missing. Theapproach can use physical or economicinformation, thus it has broad applicabilityfrom detailed economic appraisal through tothe consideration of non-market sectorswhere valuation may be challenging. It hashigh potential for identifying low and no regretoptions, and near-term adaptation strategiesthat enhance long-term resilience.• Ideally the approach should be used toconsider multiple sources of uncertainty, butthis increases the resources needed. Theapplication to climate change uncertaintyalone therefore provides a ‘lighter-touch’approach to test options for climaterobustness. In such applications, the largerthe climate uncertainties explored, the better.Where resource constraints are high, suchexercises can prove valuable for helping toidentify robust solutions and move towardsadaptive management.